Abstract The goal of this project is to validate an innovative, highly sensitive retinal eye-tracking technology, the tracking scanning laser ophthalmoscope (TSLO), as a prognostic and monitoring tool for neurodegenerative disorders, namely multiple sclerosis (MS). The applications of effective treatments for multiple sclerosis are constrained by (1) the absence of methods for early detection and (2) quantitative, highly sensitive methods monitoring deficits early in disease course when treatment may have a better chance of success. As already demonstrated, the TSLO is capable of rapidly assessing and measuring the extraordinarily fine, microscopic motion of the human eye during fixation in MS patients. Fixational eye movements are neurally-encoded, involuntary movements that require the coordination of many areas of the central nervous system. Given the TSLO?s theoretical sensitivity to change (0.2 arcminutes) and its precision of measurement - fixational eye movements have the potential utility for tracking neurodegenerative disease progression at an unprecedented scale. With the advent of the new FDA-approved MS treatment targeting B-cells (ocrelizumab), clinical tools are now desperately needed to not only assess treatment efficacy, but to objectively assess patient disability at the earliest stage of disease in order to cut relapse rates and prevent irrevocable disability. In this project, we will determine the optimal fixational eye motion metrics to distinguish patients from controls, establish the relationship between clinical disease severity measures and fixational eye movement deficits as defined by the TSLO system, and to use machine learning algorithms to further strengthen our fixational metrics.